AIMC Topic: Irritants

Clear Filters Showing 1 to 6 of 6 articles

RespiraTox - Development of a QSAR model to predict human respiratory irritants.

Regulatory toxicology and pharmacology : RTP Nov 30, 2021
Respiratory irritation is an important human health endpoint in chemical risk assessment. There are two established modes of action of respiratory irritation, 1) sensory irritation mediated by the interaction with sensory neurons, potentially stimula...
Administration, Inhalation Respiratory System Irritants Quantitative Structure-Activity Relationship Animal Testing Alternatives Machine Learning Risk Assessment
View on PubMed DOI

Machine-learning-driven biomarker discovery for the discrimination between allergic and irritant contact dermatitis.

Proceedings of the National Academy of Sciences of the United States of America Dec 14, 2020
Contact dermatitis tremendously impacts the quality of life of suffering patients. Currently, diagnostic regimes rely on allergy testing, exposure specification, and follow-up visits; however, distinguishing the clinical phenotype of irritant and all...
Leukocytes Allergens Diagnosis, Differential Skin Dermatitis, Allergic Contact Patch Tests Dermatitis, Irritant Gene Expression Regulation Irritants Male Severity of Illness Index Gene Regulatory Networks Reproducibility of Results Databases, Genetic Adult Transcriptome Biomarkers Female Machine Learning Humans Algorithms
View on PubMed DOI

Comparison of response surface methodology and artificial neural network to optimize novel ophthalmic flexible nano-liposomes: Characterization, evaluation, in vivo pharmacokinetics and molecular dynamics simulation.

Colloids and surfaces. B, Biointerfaces Aug 23, 2018
To improve the topical delivery of pilocarpine hydrochloride (PN) to treat glaucoma, flexible nano-liposomes containing PN (PN-FLs) were prepared, optimized and characterized. Artificial neural network (ANN) and response surface methodology (RSM) wer...
Spectroscopy, Fourier Transform Infrared Particle Size Molecular Dynamics Simulation Rabbits Static Electricity Drug Liberation Ophthalmic Solutions Irritants Thermodynamics Pilocarpine Neural Networks, Computer Liposomes Animals Nanoparticles
View on PubMed DOI

An in silico expert system for the identification of eye irritants.

SAR and QSAR in environmental research May 13, 2015
This report describes development of an in silico, expert rule-based method for the classification of chemicals into irritants or non-irritants to eye, as defined by the Draize test. This method was developed to screen data-poor cosmetic ingredient c...
Eye Diseases Animal Testing Alternatives Cosmetics Computer Simulation Irritants Chemical Phenomena Expert Systems Reproducibility of Results Toxicology Quantitative Structure-Activity Relationship
View on PubMed DOI

Estimation of the chemical-induced eye injury using a weight-of-evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part I: irritation potential.

Regulatory toxicology and pharmacology : RTP Dec 8, 2014
Evaluation of potential chemical-induced eye injury through irritation and corrosion is required to ensure occupational and consumer safety for industrial, household and cosmetic ingredient chemicals. The historical method for evaluating eye irritant...
Neural Networks, Computer Eye Injuries Animals Quantitative Structure-Activity Relationship Rabbits Animal Testing Alternatives Cosmetics Irritants
View on PubMed DOI

Using explainable machine learning to predict the irritation and corrosivity of chemicals on eyes and skin.

Toxicology letters May 15, 2025
Contact with specific chemicals often results in corrosive and irritative responses in the eyes and skin, playing a pivotal role in assessing the potential hazards of personal care products, cosmetics, and industrial chemicals to human health. While ...
Risk Assessment Humans Caustics Machine Learning Skin Animal Testing Alternatives Computer Simulation Cosmetics Eye Animals Irritants
View on PubMed DOI
Popular Topics
Recent Journals